NCT04130789

Personalized Swiss Sepsis Study

Personalized Swiss Sepsis Study: With Machine Learning and Computational Modelling Towards Personalized Sepsis Management - Discovery of Digital Biomarkers

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 17,500 (estimated)
• Sponsor: University Hospital, Basel, Switzerland · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

This multi-center study is to focus on patients with sepsis in Intensive Care Units (ICUs) in order to better understand the complex host-pathogen interaction and clinical heterogeneity associated with sepsis. Understanding this heterogeneity may allow the development of novel diagnostic approaches. Data from patients will be analyzed using state-of-the art analytical algorithms for biomarker discovery including machine learning and multidimensional mathematical modelling to explore the large datasets generated. In order to discover digital biomarkers for the study endpoints a case-control study design will be used to compare data patterns from patients with sepsis (cases) and those without sepsis (controls).

Conditions

• Sepsis

Interventions

Type	Name	Description
OTHER	compare data patterns by data-driven algorithms to determine sepsis	compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to reliably determine sepsis
OTHER	compare data patterns by data-driven algorithms to predict sepsis-related mortality	compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to to predict sepsis-related mortality

Timeline

• Start date: 2019-11-15
• Primary completion: 2022-05-31
• Completion: 2025-12-01
• First posted: 2019-10-17
• Last updated: 2025-03-05

Locations

16 sites across 1 country: Switzerland